Inverse Synthetic Aperture Radar (ISAR) is a technique for high-resolution imaging of radar objects. A radar system supplies a sequence of images of moving objects. The radar images may have a striking likeness with the visual image of an object, and an operator may then perform manual classification of the object by visual analysis of the ISAR image. However, in a rapidly developing situation with many objects present on the radar screen, the operator will have very short time available to perform a correct classification. It would be very desirous to have an automatic tool available for classifying ISAR objects. This would reduce the radar operator workload, and lead to a more efficient use of the radar.
From literature there is known several method for automatic ship classification. In Musman, S.; Kerr, D.; Bachmann, C.; Automatic Recognition of ISAR ship images, IEEE Transactions on Aerospace and Electronic Systems, Vol. 32, No. 4, October 1996, pp. 1392-1403, there is presented a method based on comparing the shape of an object with wire-frame models.
A different implementation of this method is described in Knapskog, A. O.; Automatic Classification of Ships in ISAR Images Using Wire-Frame Models, Proceedings 5th European Conference on Synthetic Aperture Radar, 953-956. In this method the ISAR image of an object is compared with wire-frame models of possible objects stored in a database. Before a comparison is made, the orientation of the object in the ISAR image is found by analysing prominent features of the hull, e.g. the ship's centreline and positions of the hull sides, and candidate models in the database are transformed into the same orientation. Silhouettes of the observed object and the models are extracted and compared.
In the existing method each relevant model in the model database must be transformed for each ISAR object image. This makes the method rather slow, which makes it not suitable for real time classification.
Also, the method is vulnerable to inaccurate estimation of certain features. For example a ship centreline can be found by fitting a straight line through the object by the method of least squares. Tall structures (e.g. a mast) on the object will affect the least squares line fit. By manual operation the effect may be reduced. The hull side is found by fitting a second-degree curve to the side of the side of the object by the method of least squares. Often only one (the near-) side is visible on the ISAR image. The invisible side would then have to be found by mirroring the near side of the object. This makes the existing method not suitable for automatic and real-time classification of radar objects.